VisCollage: Annotative Collages for Organizing Data Event Charts

Xiao Han Li*, Yi Ting Hung, Jia Yu Pan, Wen Chieh Lin

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

While existing visualization systems excel in exploring datasets and discovering data patterns and insights, challenges remain in automatically generating infographics from exploration-derived visualizations. We propose VisCollage, a computational pipeline that automatically organizes and renders charts from an exploration in a 'visual collage', which is inspired by data journalism and can be viewed as a kind of 'partitioned poster infographic'. By analyzing the relation (e.g., drill-down or comparison) between charts established during exploration, VisCollage groups and merges them to reduce data redundancy. In addition, VisCollage automatically identifies a main chart of the exploration and arranges annotations and background charts around it. User studies evaluated from the perspectives of creators, professional data journalists, and general readers indicate that our system assists creators in generating satisfactory visualization summaries of data events, enables the general audience to extract insights from the data through visual collages, and are well received by professionals.

原文English
主出版物標題Proceedings - 2024 IEEE 17th Pacific Visualization Conference, PacificVis 2024
發行者IEEE Computer Society
頁面262-271
頁數10
ISBN(電子)9798350393804
DOIs
出版狀態Published - 2024
事件17th IEEE Pacific Visualization Conference, PacificVis 2024 - Tokyo, 日本
持續時間: 23 4月 202426 4月 2024

出版系列

名字IEEE Pacific Visualization Symposium
ISSN(列印)2165-8765
ISSN(電子)2165-8773

Conference

Conference17th IEEE Pacific Visualization Conference, PacificVis 2024
國家/地區日本
城市Tokyo
期間23/04/2426/04/24

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